Study: Automation Drives Income Inequality | MIT News
When you use self-checkouts in supermarkets and pharmacies, you’re probably not doing – with all due respect – a better job of packing your purchases than cashiers once did. Automation simply makes bagging cheaper for large retail chains.
“If you introduce self-service payment terminals, it won’t make a big difference to productivity,” says MIT economist Daron Acemoglu. However, in terms of lost wages for employees, he adds, “this will have quite significant distributional effects, especially for low-skilled service workers. It is a labor transfer device, rather than a productivity increase device. »
A recently published study co-authored by Acemoglu quantifies the extent to which automation has contributed to income inequality in the United States, simply by replacing workers with technology – be it self-checkouts, call center systems, assembly line technologies or other devices. . Over the past four decades, the income gap between the most educated and the least educated has widened considerably; the study reveals that automation accounts for more than half of this increase.
“This single variable…explains 50-70% of the changes or variations between group inequalities from 1980 to about 2016,” says Acemoglu.
The article, “Tasks, Automation, and the Rise in US Wage Inequality”, is published in Econometrics. The authors are Acemoglu, who is an institute professor at MIT, and Pascual Restrepo PhD ’16, assistant professor of economics at Boston University.
So much “passable automation”
Since 1980 in the United States, the inflation-adjusted earnings of college and postgraduate graduates have increased dramatically, while the inflation-adjusted earnings of men without a high school diploma have fallen by 15%.
How much of this change is due to automation? Rising income inequality could also stem from, among other things, the decreasing prevalence of unions, market concentration resulting in a lack of competition for labor or other types of technological change.
To conduct the study, Acemoglu and Restrepo used statistics from the United States Bureau of Economic Analysis on the extent to which human labor was used in 49 industries from 1987 to 2016, as well as data on machinery and equipment. software adopted at that time. The researchers also used data they had previously compiled on robot adoption in the United States from 1993 to 2014. In previous studies, Acemoglu and Restrepo found that robots have on their own replaced a significant number of workers in the USA, helped some companies dominate their industriesand contributed to inequality.
At the same time, the researchers used U.S. Census Bureau measures, including its American Community Survey data, to track worker outcomes during that time for about 500 demographic subgroups, broken down by gender, education, age, race and ethnicity, and immigration status, while examining employment, inflation-adjusted hourly wages, and more from 1980 to 2016. Examining the links between changes in business practices and changes in labor market outcomes, the study can estimate the impact of automation on workers.
Ultimately, Acemoglu and Restrepo conclude that the effects were profound. Since 1980, for example, they estimate that automation has reduced the wages of men without a high school diploma by 8.8% and women without a high school diploma by 2.3%, adjusted for inflation.
A central conceptual point, says Acemoglu, is that automation needs to be viewed differently from other forms of innovation, with its own distinct effects on workplaces, and not just as part of a larger trend towards implementation of technology in everyday life in general.
Consider those self-checkout kiosks again. Acemoglu calls these types of tools “technology means” or “automation means”, because of the trade-offs they contain: such innovations are good for business results, bad for employees in the service industry and not extremely significant in terms of overall productivity gains, a true marker of an innovation likely to improve our overall quality of life.
“Technological change which creates or increases the productivity of industry, or the productivity of a type of labor, creates [those] large productivity gains but does not have huge distributional effects,” says Acemoglu. “In contrast, automation creates very large distributional effects and may not have large effects on productivity.”
A new perspective on the big picture
The results occupy a special place in the literature on automation and employment. Some popular tech narratives have predicted near-total job cuts in the future. Alternatively, many researchers have developed a more nuanced picture, in which technology disproportionately benefits highly skilled workers, but also produces important complementarities between high-tech tools and labor.
The current study differs at least in degree with this latter picture, presenting a more austere perspective in which automation reduces workers’ earning power and potentially reduces the extent to which policy solutions – more bargaining power for workers , less market concentration – could mitigate the adverse effects of automation on wages.
“These are controversial results in the sense that they imply a much larger effect for automation than anyone thought, and they also imply less explanatory power for other [factors]says Acemoglu.
Yet, he adds, in an effort to identify the drivers of income inequality, the study “does not completely avoid other non-technological theories. Moreover, the pace of automation is often influenced by various institutional factors, including the bargaining power of workers.
Labor economists say the study is an important addition to the literature on automation, work and inequality, and should be taken into account in future discussions of these issues.
“Acemoglu and Restrepo’s paper offers an elegant new theoretical framework for understanding the potentially complex effects of technical change on the aggregate wage structure,” says Patrick Kline, professor of economics at the University of California, Berkeley. “Their empirical finding that automation has been the single largest driver of wage dispersion in the United States since 1980 is intriguing and seems certain to rekindle the debate about the relative roles of technical change and labor market institutions in the generation of wage inequality.
For their part, in the article, Acemoglu and Restrepo identify several directions for future research. This includes studying the response over time of firms and workers to increased automation; the quantitative effects of technologies that create jobs; and industry competition between companies that quickly adopted automation and those that did not.
The research was supported in part by Google, the Hewlett Foundation, Microsoft, the National Science Foundation, Schmidt Sciences, the Sloan Foundation, and the Smith Richardson Foundation.